Knowledge Science, Engineering and Management


 in this work, a new personalized reviews’ selection is proposed. We based on the idea of that different point of view for the user causes different evaluation and revering. For this reason, searching on the best reviews in a specific subject gives more accurate and significant selection results. In this paper, design a new approach for the best personalized reviews’ selection that is based on two stages. The first one in the predict the subject aspect modeling (distribution) based on using the A latent Dirichlet allocation (LDA) model. Second, we design a new weighted personalized reviews selection based subject aspect scoring function to select the top personalized reviews.